Carolyn Olsen
Carolyn Olsen developed HiveGuide as an independent open-source project to solve practical field inspection challenges in beekeeping and generalized for broader scientific applications. In her day role, she is Director of Data Science at The Hartford, where she leads an AI Accelerator for two business areas, helping them leverage generative AI. Previously VP of Data Science at Clearcover, she has extensive experience developing production AI systems including LLM-powered tools, supervised ML models, and reinforcement learning models. She holds a Master of Science in Applied Economics from Marquette University and served 8 years in the U.S. Coast Guard Reserve.
Session
Field inspections in agriculture and science face a common problem: hands are full, data needs structure, and decisions require both inspection history and domain expertise. I built HiveGuide, an open-source field inspection system with three main components: (1) voice transcription for hands-free data entry, (2) AI extraction to structured data and action items, and (3) an AI assistant that provides intelligent advice by routing between personal inspection history and authoritative domain literature. For the assistant, I tested 7 routing strategies on 500+ queries to solve a dual-source problem: when to query your data versus domain references. The LLM classifier approach balanced accuracy and speed without requiring training data. The architecture is transferable to any inspection domain where you need minimal device interaction and intelligent advising.